Among the most fascinating abilities of human beings is their propensity to verbalize, communicate and adopt ideas within a vast network of social contacts. Human cognitive capabilities are uniquely suited to communication, and they are crucial to the intelligence emerging from human communities. Despite much work and much progress in the field, the cognitive and psycholinguistic mechanisms underlying language comprehension and production are still poorly understood. While recent studies paint a picture of how memory and contextualization help humans to develop a rapid understanding of a dialogue partner's ideas and individual language, we do not understand whether human memory has evolved to support team-work and social cognition.

Cognitive modeling and network simulation techniques have allowed a recent growth in interest for the interaction of cognitive mechanisms with the social environment. Individuals adapt their linguistic expressions quickly to their interaction partners, and new communicative standards may soon spread through a network of connected agents. Cognitive modeling frameworks, validated and refined through careful experimentation, as well as computational tools now allow the larger-scale simulation of human societies and the uptake of existing language resources (corpora) in the quest for the architecture of the human language faculty. Adopting datasets collected in real-life situations allows us to test cognitive and psycholinguistic models. Once validated, they will make better predictions and cover broad ranges of human behavior. Broad coverage and large-scale simulation require new computational tools, new methodologies, new datasets and new experimental designs.

My academic interests span computer science, linguistics and cognitive science. For example, I employ data-driven computational methods to test psycholinguistic hypotheses. I use small- and large-scale cognitive simulation (e.g., with ACT-R) to model learning and adaptation in human subjects, specifically during interaction within pairs and larger groups. I am familiar with computational and statistical modeling techniques, but I also do experimental work.

I am currently a postdoctoral researcher at Carnegie Mellon University, Department of Psychology. In 2008, I completed my PhD in Cognitive Science from the School of Informatics, University of Edinburgh under Johanna Moore and Frank Keller. My PhD thesis investigates structural priming and alignment effects in human-human dialogue. Using large corpora and linear modeling techniques I demonstrate the relationship between success in dialogue and a simple tendency to repeat linguistic decisions at the lexical/syntactic level. The methodology developed to measure priming is used to determine architectural properties of the comprehension and production apparatus, in particular with respect to hierarchical structure, and flexible incrementality of syntactic processing. This leads to a model of natural language production using a standard cognitive architecture, which can explain syntactic priming as lexical learning effect.

I hold a "Diplom" in Linguistics from Potsdam, Germany and an MSc in Computer Science from University College Dublin, Ireland. I have worked on multimodal human-computer interaction during a two-year Research Fellowship at MIT Media Lab Europe. (See: Publications.) I also have industry experience in programming, online services, language technology and as a radio journalist.

I created and continue to lead the free software project Aquamacs Emacs, used in many university labs world-wide. I'm a licensed glider pilot and have been flying in Pennsylvania and Scotland.

Contact: David Reitter, Carnegie Mellon University. E-mail or